12,565 research outputs found
Going Beyond Counting First Authors in Author Co-citation Analysis
No full textThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Dispelling the Myths Behind First-author Citation Counts
No full textWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
Supplemental Material - Novel deoxyribonucleic acid methylation perturbations in workers exposed to vinyl chloride novel deoxyribonucleic acid methylation changes exposed to vinyl chloridein workers
No full textSupplemental Material for Novel deoxyribonucleic acid methylation perturbations in workers exposed to vinyl chloride novel deoxyribonucleic acid methylation changes exposed to vinyl chloridein workers by Xiaotian Zhao, Yan Hao, Qian Wang, Yongmei Shen, Ying Cheng, Ben Li, Yi Gao, Tong Wang, Yulan Qiu in Toxicology and Industrial Health</p
Raw data of Zhao et al., 2022, Geoderma
No full textRaw data associated with Zhao et al., 2022, Geoderma. Any use of the data set should be approved by the corresponding author Kai Yue at "[email protected]".</p
Enantioselective organocatalytic conjugate addition of amines to ?,?-unsaturated aldehydes: one-pot asymmetric synthesis of ?-amino acids and 1,3-diamines
No full textOrganocatalytic asymmetric amine conjugate additions to ?,?-unsaturated aldehydes catalyzed by protected diarylprolinols are presented. The reactions proceed with high enantioselectivity and result in Cbz or Boc protected ?-amino aldehydes, ?-amino alcohols, ?-amino acids and 1,3-diamines with typically 82–99% ee
Chao Yuen Ren (1892–1982)
No full textY. R. Chao is easily the most famous linguist to have come out of China. Born before the end of the last dynasty in China, he received a traditional Confucian education, but was also one of the first Chinese people to be sent to the West for training in modern Western science (under the Boxer Indemnity Fund). The remarkable breadth and scope of his studies included physics, mathematics, linguistics, musical and literary composition, and translation, and he was a pioneer in many of these fields
Heteroepitaxial Growth of 3C-SiC Films on Maskless Patterned Silicon Substrates
No full textHeteroepitaxial growth of 3C-SiC on patterned Si substrates by low pressure chemical vapor deposition (LPCVD) has been investigated to improve the crystal quality of 3C-SiC films. Si substrates were patterned with parallel lines, 1 to 10μm wide and spaced 1 to 10μm apart, which was carried out by photolithography and reactive ion etching. Growth behavior on the patterned substrates was systematically studied by scanning electron microscopy (SEM). An air gap structure and a spherical shape were formed on the patterned Si substrates with different dimensions. The air gap formed after coalescence reduced the stress in the 3C-SiC films, solving the wafer warp and making it possible to grow thicker films. XRD patterns indicated that the films grown on the maskless patterned Si substrates were mainly composed of crystal planes with (111) orientation
Gated relational stacked denoising autoencoder with localized author embedding for global citation recommendation
No full textCitation recommendation is an effective and efficient way to facilitate authors finding desired references. This paper presents a novel neural network based model, called gated relational probabilistic stacked denoising autoencoder with localized author (GRSLA) embedding, for global citation recommendation task. Our model is comprised of two modules with different neural network architecture. For each citing and cited papers, we use a gated paper embedding module, which is extended from probabilistic stacked denoising autoencoder (PSDAE) by adding gated units, to obtain their paper vectors. The added gated units are able to utilize text information of cited paper to refine the vector representation of citing paper in multiple semantic levels. For an author in papers, we first apply topic model to obtain his/her semantic neighbors, and then use a localized author embedding (LAE) module to excavate author vector representation from semantic and explicit neighbors. Unlike most graph convolutional network (GCN) based methods, the LAE module is able to avoid computing global Laplacian in whole graph by taking limited neighbors. Moreover, the LAE module can also be stacked to absorb more neighbors, which makes our model have high extendibility. Based on the generation process of GRSLA, we also derive a learning algorithm of our model by maximum a posteriori (MAP) estimation. We conduct experiments on the AAN, DBLP and CORD-19 datasets, and the results show that GRSLA model works well than previous global citation recommendation methods
Recyclable three-dimensional Ag nanoparticle-decorated TiO2 nanorod arrays for surface-enhanced Raman scattering
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